From breathing to sleep, the human body functions through cycles. Researchers attain the most accurate physiological data when analyzing subjects through cyclic data. Wandering baselines, non-AC coupled, and varying peak amplitudes are some of the many challenges that get in the way of cyclic data analysis. Researchers can overcome these problems with careful goal planning combined with physiology analysis software.
The first step for researchers to take is to define their goals, as a clear strategy is necessary to assess accurate data. One example of a goal could be to extract the average heart rate for each thirty-second interval from BP data. The researcher would first split the problem into multiple steps and classify data between systolic and diastolic locations. Classification would differentiate the primary and intra-cycle locations of interest and the researcher would want the systolic and diastolic peaks for moving averages.
With the Find Cycle Peak Detector, researchers can do this automatically. The AcqKnowledge Find Cycle Peak Detector extracts heart rate and triggers a traceable spike train. With AcqKnowledge, researchers can separate bpm data rates to determine the diastolic and systolic patterns. Individual means, taken by AcqKnowledge, reveal various physiological cycles, including the data rates mentioned above.
The Find Cycle Peak Detector opens the door for researchers to advance their studies in a comprehensive range of fields. Although physiological signals take longer to identify and analyze, the ability to differentiate data sets helps to determine the derivatives and construct signals appropriate for the analysis of the bodily cycle of interest. Physiology technology, such as the Find Cycle Peak Detector, improves the cyclic research procedures because information processes fast and effectively.
BIOPAC’s AcqKnowledge software analyzes data cycles by rates, periodicities, and precise data analysis such as ECG or NICO. Researchers can expedite lab workflow with BIOPAC’s basic scripting to expeditiously detect complex multi-step physiological cycles. The built-in domain-specific analysis and general-purpose tools, such as epoch analysis and stimulation-response analysis, provide researchers with the data they need almost instantly. Scientists can also synchronize various data sets at once with AcqKnowledge software.
AcqKnowledge software is an extremely powerful tool, capable of automatically analyzing data for a variety of applications. To find learn more about AcqKnowledge Find Cycle Detector or view useful analysis tips and tricks, visit the BIOPAC webinar page.